Numerical simulation based science follows a new paradigm: its knowledge discovery process rests upon massive amounts of data. We are entering the age of data intensive science. Climate scientists generate data faster than can be interpreted and need to prepare for further exponential data increases. Current analysis approaches are primarily focused on traditional methods, best suited for large-scale phenomena and coarse-resolution data sets. Tools that employ a combination of high-performance analytics, with algorithms motivated by network science, nonlinear dynamics and statistics, as well as data mining and machine learning, could provide unique insights into challenging features of the Earth system, including extreme events and chaotic regimes. The breakthroughs needed to address these challenges will come from collaborative efforts involving several disciplines, including end-user scientists, computer and computational scientists, computing engineers, and mathematicians.

The SC11 CKD workshop will bring together experts from various domains to investigate the use and application of large-scale graph analytics, semantic technologies and knowledge discovery algorithms in climate science. The workshop is the second in a series of planned workshops to discuss the design and development of methods and tools for knowledge discovery in climate science.

The first Climate Knowledge Discovery (CKD) workshop was hosted by the German Climate Computing Center (DKRZ) in Hamburg, Germany from 30 March to 1 April 2011. This workshop brought together climate and computer scientists from major US and European laboratories, data centers and universities, as well as representatives from the industry, the broader academic, and the Semantic Web communities. Papers and presentations are available online.

We hope that you will be able to participate and look forward to seeing you in Seattle. For further information or questions, please do not hesitate to contact any of the co-organizers: